def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) y = parsed_args.slice_yplus if y: print('Hello! ', y) in_dir = "/home/mknorps/Projects/ForPhD/SPECTRAL_from2011/FRACTAL/" out_dir = "/home/mknorps/Projects/ForPhD/SPECTRAL_from2011/FRACTAL/slices/" f_min = 880 f_max = 900 for ptype in range(4): for i in range(f_min, f_max): input_file = 'particles_0{}'.format(i) output_file_core = "slice_FRACTAL_center_{}_{}".format( p.StList2[ptype], i) cut_with_halo(in_dir, out_dir, input_file, output_file_core, ptype, yplus=145)
def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) y = parsed_args.slice_yplus if y: print('Hello! ', y) s.write_to_file(f.file_path_write) s.symmetrise(f.file_path_write, f.file_path_symm) d.draw_diss_tot(f.file_path_symm, f.file_path_main + "diss.pdf") d.draw_diss_model(f.file_path_symm, f.file_path_main + "diss_model.pdf")
def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) y = parsed_args.slice_yplus if y: print('Hello! ', y) #s.write_to_file(f.file_path_write) data = d.DrawU2sgs() data.draw_u2sgs(f.file_path_main + "u2sgs.pdf") data.draw_ksgs(f.file_path_main + "ksgs.pdf") data.draw_sigma_check(f.file_path_main + "sigma_check.pdf")
def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) # ct = parsed_args.particle_type #ts.write_to_file(f.file_path_write, symm=False) #ts.write_to_file(f.file_path_write_symm) data = pd.read_csv(f.file_path_write) data_symm = pd.read_csv(f.file_path_write_symm) td.draw_tau(data, f.data_path + "test.pdf") td.draw_tau_symm(data_symm, f.data_path + "model_tausg_symm.pdf") optimal = ts.optimize_tau_fluid(f.file_path_write_symm)
def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) y = parsed_args.slice_yplus if y: print('Hello! ', y) # for key in f.prange.keys(): # c.write_to_file(f.file_path_write+key+".csv",key) data = draw.Draw() # data.draw_ur(f.file_path_main + "ur.pdf") # data.draw_urnorm2(f.file_path_main + "urnorm2.pdf") data.draw_alpha(f.file_path_main + "alpha.pdf")
def run_project(args): opt = options.Options() parsed_args = opt.parse(args[1:]) y = parsed_args.slice_yplus d1 = 2**(-1 / 3) d2 = -2**(-1 / 3) w3_LES = fractal_interpolation(at.w(Ufx, d1, d2, 3), len(Ufx)) w3_from_resampled = fractal_interpolation(at.w(Ux_resampled, d1, d2, 3), len(Ufx)) label = {0: '$W^{3}$: filtered DNS', 1: '$W^{3}$: resampled DNS'} draw_fractal('LES_and_resampled.pdf', w3_LES, w3_from_resampled, label=label) draw_fractal('LES_and_DNS.pdf') ek = kinetic_energy(Ux, Ufx, Ux_resampled, w3_LES['y'], w3_from_resampled['y']) fft = fourier_transform(Ux, Ufx, Ux_resampled, w3_LES['y'], w3_from_resampled['y']) plt.figure(figsize=(8, 4)) sns.violinplot(data=list(fft.values())[:3]) plt.xticks(plt.xticks()[0], fft.keys()) plt.tight_layout() plt.savefig("fractal_violinplot_ftt.pdf") for_box = { 'DNS': Ux, 'filtered DNS': Ufx, '$W^{3}$: filtered': w3_LES['y'], 'resampled DNS': Ux_resampled, '$W^{3}$: resampled': w3_from_resampled['y'] } colors = { i: v for i, v in enumerate( ['lightgrey', 'lightgrey', 'darkorange', 'lightgrey', 'slateblue']) } plt.figure(figsize=(8, 4)) sns.violinplot(data=list(for_box.values()), orient='v', palette=colors, inner='quartile', bw='silverman') plt.xticks(plt.xticks()[0], for_box.keys()) plt.tight_layout() plt.savefig("fractal_violinplot.pdf") plt.figure(figsize=(8, 4)) sns.boxplot(data=list(for_box.values())) plt.xticks(plt.xticks()[0], for_box.keys()) plt.tight_layout() plt.savefig("fractal_boxplot.pdf")